RestraintMaker: a graph-based approach to select distance restraints in free-energy calculations with dual topology

Author:

Ries BenjaminORCID,Rieder SaloméORCID,Rhiner Clemens,Hünenberger Philippe H.ORCID,Riniker SereinaORCID

Abstract

AbstractThe calculation of relative binding free energies (RBFE) involves the choice of the end-state/system representation, of a sampling approach, and of a free-energy estimator. System representations are usually termed “single topology” or “dual topology”. As the terminology is often used ambiguously in the literature, a systematic categorization of the system representations is proposed here. In the dual-topology approach, the molecules are simulated as separate molecules. Such an approach is relatively easy to automate for high-throughput RBFE calculations compared to the single-topology approach. Distance restraints are commonly applied to prevent the molecules from drifting apart, thereby improving the sampling efficiency. In this study, we introduce the program RestraintMaker, which relies on a greedy algorithm to find (locally) optimal distance restraints between pairs of atoms based on geometric measures. The algorithm is further extended for multi-state methods such as enveloping distribution sampling (EDS) or multi-site$$\lambda $$λ-dynamics. The performance of RestraintMaker is demonstrated for toy models and for the calculation of relative hydration free energies. The Python program can be used in script form or through an interactive GUI within PyMol. The selected distance restraints can be written out in GROMOS or GROMACS file formats. Additionally, the program provides a human-readable JSON format that can easily be parsed and processed further. The code of RestraintMaker is freely available on GitHubhttps://github.com/rinikerlab/restraintmaker.

Funder

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung

Swiss Federal Institute of Technology Zurich

Publisher

Springer Science and Business Media LLC

Subject

Physical and Theoretical Chemistry,Computer Science Applications,Drug Discovery

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